Results 61 to 70 of about 25,451 (177)

Exploring a Subpopulation of MASLD Associated With New Onset of CKD Using Supervised Clustering Techniques

Hepatology Research, EarlyView.
The supervised clustering of metabolic dysfunction‐associated steatotic liver disease (MASLD) using a SHapley Additive exPlanations (SHAP)‐converted matrix reveals distinct subpopulations that improved risk stratification for new onset of chronic kidney disease (CKD).
Itaru Hosaka, Marenao Tanaka, Tatsuya Sato, Yukinori Akiyama, Keitaro Nishizawa, Rie Matsumori, Hiroki Aida, Wataru Kawaharata, Kei Nakata, Koki Abe, Toru Suzuki, Hidemichi Kouzu, Naoya Yama, Nagisa Hanawa, Masato Furuhashi   +14 more
wiley   +1 more source

Statistical errors and reporting deficiencies in clinical prosthodontic publications, 2019-2024. [PDF]

J Prosthodont
Abstract Purpose Evidence‐based dentistry relies on valid statistics, yet misuse remains common. Despite increased emphasis on statistical rigor, recent prosthodontic publications remain underexplored. We hypothesized that statistical misapplications and reporting deficiencies persist in prosthodontic research. This study evaluated the appropriateness,
Ben Suleiman A, Shuler CF, Hieawy A, von Bergmann H.   +3 more
europepmc   +2 more sources

Deconvolution Estimation in Measurement Error Models: The R Package decon [PDF]

Data from many scientific areas often come with measurement error. Density or distribution function estimation from contaminated data and nonparametric regression with errors in variables are two important topics in measurement error models.
Bin Wang, Xiao-Feng Wang
core   +1 more source

Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation

International Statistical Review, EarlyView.
Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo, Domingo Morales, Nicola Salvati, Francesco Schirripa Spagnolo   +3 more
wiley   +1 more source

Serum nonmercaptalbumin to total albumin ratio and bilirubin predict ADL decline in older adults with type 2 diabetes

Journal of Diabetes Investigation, EarlyView.
In a longitudinal cohort of older adults with type 2 diabetes, incident ADL disability was evaluated. Higher HNA%, lower serum bilirubin, and older age independently predicted the risk of disability. Their combined assessment may offer clinically useful tools for identifying individuals at elevated risk of functional deterioration.
Yukihiro Inoguchi, Toyoshi Inoguchi, Keiko Yasukawa, Saki Fukuhara, Tomoaki Etoh, Mitsunori Masakado, Mayumi Yamato, Fumio Umeda, Yutaka Yatomi, Teruaki Yamauchi, Masatoshi Nomura   +10 more
wiley   +1 more source

Heterogeneity in Manufacturing Growth Risk

Journal of Money, Credit and Banking, EarlyView.
Abstract We analyze differences in output growth risk with respect to financial conditions across U.S. manufacturing industries. Using a multilevel quantile regression approach, we find that industries exhibit heterogeneous increases of downside risk in times of tight financial conditions, while upside potential remains stable.
DAAN OPSCHOOR, DICK VAN DIJK, PHILIP HANS FRANSES   +2 more
wiley   +1 more source

Validation of machine learning based scenario generators

Journal of Risk and Insurance, EarlyView.
Abstract Machine learning (ML) methods are becoming increasingly important for designing economic scenario generators for internal models. Validating data‐driven models requires different methods than validating classical, theory‐based models. We discuss two novel aspects of such validation: first, checking the multivariate distribution of risk factors,
Gero Junike, Solveig Flaig, Ralf Werner
wiley   +1 more source

Measures of Analysis of Time Series (MATS): A MATLAB Toolkit for Computation of Multiple Measures on Time Series Data Bases [PDF]

In many applications, such as physiology and finance, large time series data bases are to be analyzed requiring the computation of linear, nonlinear and other measures.
Alkiviadis Tsimpiris, Dimitris Kugiumtzis   +1 more
core   +1 more source

Automated Bandwidth Selection for Inference in Linear Models With Time‐Varying Coefficients

Journal of Time Series Analysis, EarlyView.
ABSTRACT The problem of selecting the smoothing parameter, or bandwidth, for kernel‐based estimators of time‐varying coefficients in linear models with possibly endogenous explanatory variables is considered. We examine automated bandwidth selection by means of cross‐validation, a nonparametric variant of Akaike's information criterion, and bootstrap ...
Charisios Grivas, Zacharias Psaradakis
wiley   +1 more source

Functional Vašiček Model

Journal of Time Series Analysis, EarlyView.
ABSTRACT We propose a new formulation of the Vašičekmodel within the framework of functional data analysis. We treat observations (continuous‐time rates) within a suitably defined trading day as a single statistical object. We then consider a sequence of such objects, indexed by day.
Piotr Kokoszka, Neda Mohammadi, Leonardo Santoro, Hong Miao, Haonan Wang   +4 more
wiley   +1 more source